無線感測網路為一項近年來新興的無線通訊技術，並且具有相當多樣化的應用，例如環境監控、感測目標物定位與追蹤、個人健康控管等等。而分散式估計則是無線感測網路技術的重要應用之一。在分散式估計中，眾多感測器被佈放在特定的感測區域內，以共同執行針對一未知信號源的信號感測與估計。感測器基本上為具備感測功能與無線通訊能力，且由電池驅動之低成本設備。由於感測器上的電源供應相當有限，因此為了延長無線感測網路之生命週期，感測器上能源的節約便成為非常重要的議題。在此篇論文中，我們實際考慮了無線感測網路環境下受雜訊干擾的信號觀測及訊息傳送，提出了應用於無線感測網路分散式估計中的節能合作式訊息聚集方法。在此節能合作式訊息聚集方法內，每一次的信號估計過程中，每一個感測點針對其本地信號觀測，只需傳送單位元資料至資料融合中心，藉由傳送訊息長度的最小化來大幅降低使用在訊息傳送上的能量消耗。另外，錯誤更正碼的概念亦被運用在我們所提出的合作式訊息聚集方法中，藉以提供對於信號觀測資訊的保護。
在本論文的第一個主題中，我們使用了重覆碼的技術作為對於信號觀測資訊的保護機制。每一個感測點將其本地信號觀測量化為多位元訊息後，從中選取一個位元的資料並轉送至資料融合中心。我們分別提出了硬決策估計子與最大似然估計子，作為合作式訊息聚集方法中資料融合中心針對所有感測點所轉送訊息位元的融合規則。其中，重覆碼的設計對應到針對每個感測點所轉送量化訊息位元的安排，我們將所提兩種估計子中的轉送位元安排視為一個資源分配問題來探討。藉由將此資源分配問題轉化為凸函數最佳化問題來求解，我們分別針對兩種估計子推導出其對應的次最佳資源分配對策。經由模擬結果，我們證明了所推導出的兩種次最佳資源分配皆為彈性式資源分配對策，可基於不同的系統狀況調整其資源分配結果，同時亦能提供相較於其他固定式資源分配對策更佳的信號估計表現。另外，我們也證明了在這個主題中所提出的兩種合作式訊息聚集方法，在考慮不完美傳送通道的無線感測環境下，可表現出相較於其他我們所參考的既有分散式估計方法更佳的估計效能。
在第二個主題中，我們討論了在序列合作式訊息聚集方法中浮現的對於能源節約與估計效能提升的取捨問題。在序列合作式訊息聚集方法中，我們應用了序列式訊息轉送來取代批次式訊息轉送。在資料融合中心所進行的資料融合運算則是基於硬決策估計子，並包含數個序列式執行的投票程序，其中每一個投票程序皆負責量化信號觀測中一個特定位元的檢測任務。在系統初始化階段，為了執行基於多數決原則下，對於量化信號觀測中每一個位元的檢測，每一個投票程序皆被適當地分配了一定比例的感測點數量。由於每一個投票程序中所被分配的所有感測點皆以序列方式轉送它們的訊息位元至資料融合中心，因此每一個投票程序皆可能在僅收集部分的訊息位元資料後，就因為已滿足多數決原則而完成其檢測任務。而在該投票程序中，由於檢測任務提前完成而不需轉送其訊息位元的感測點，則被視為未使用資源。對於投票程序中未使用資源的管理，我們分別設計了節能演算法與估計效能提升演算法。針對節能演算法中的總能量消耗，我們亦經由分析與推導而得出其理論值。從模擬結果中可以發現，相較於批次合作式訊息聚集方法，我們針對序列合作式訊息聚集方法所提出的節能演算法與估計效能提升演算法，的確能夠有效率地分別節省能源的消耗與提升信號估計的效能。同時，經由與模擬結果的比對，我們針對節能演算法中總能量消耗所推導出的理論值亦得到驗證。
在本論文的第三個主題中，以提升原本基於重覆碼的合作式訊息聚集方法的估計效能為出發點，我們針對採用其他具有更佳除錯效能的錯誤更正碼進行研究。在考慮到對於提升錯誤更正效能與抑制觀測雜訊影響的取捨問題下，我們採用了低密度產生矩陣碼並且提出基於低密度產生矩陣碼的合作式訊息聚集方法。在此方法中，每一個感測點上轉送位元的產生為一個可預先決定且具有極低運算複雜度的信號觀測編碼程序。另外，考慮到產生矩陣中短迴圈的存在會造成錯誤更正效能的衰退，我們也針對產生矩陣的建構，提出了一個具有完全消除長度為4的短迴圈能力的建構方法。經由模擬結果，我們證明了基於低密度產生矩陣碼的合作式訊息聚集方法，相較於基於重覆碼的合作式訊息聚集方法，具有更佳的信號估計表現。對於無線感測環境中可能發生的感測點隨機死亡的狀況，我們所提出基於低密度產生矩陣碼的合作式訊息聚集方法亦具有很好的抵抗能力。

Wireless sensor networks (WSN) is an emerging technology in recent years that has a wide variety of applications, such as environmental surveillance, target locating and tracking, and personal health care. Distributed estimation is one of the most interesting applications in WSNs, where spatially distributed sensors are deployed over the sensing area to estimate an unknown signal. Sensors are basically low-cost devices that are endowed with the sensing function and the wireless communication ability, and powered by the batteries. The battery-driven sensors are typically subject to stringent energy constraints; hence, energy conservation is a crucial issue for extending the network lifetime in WSNs. In this dissertation, we consider the effects of noisy observations and imperfect information transmissions, and propose energy-efficient cooperative information aggregation (CIA) schemes for distributed estimation in WSNs. In the CIA schemes, each node sends only one bit, representing its local observation, to the fusion center (FC) in each estimation procedure to reduce the transmission energy consumption. In addition, the concept of error correction codes is incorporated into the design of CIA schemes to provide the observation protection.
In the first part of this dissertation, we use the technique of repetition codes for observation protection. Each node quantizes its local observation into multiple bits and then selects one of the resultant bits to forward to the FC. Two estimators, the hard decision estimator (HDE) and the maximum likelihood estimator (MLE), are proposed as the fusion rules performed at the FC in the CIA schemes. The design of the applied repetition codes corresponds to the arrangement for the forwarded bit at each node; the forwarded bit arrangements for the HDE and the MLE are formulated as a resource allocation problem to investigate. By solving the convex optimization problem transformed from the resource allocation problem, the suboptimal resource allocation (SORA) for HDE and the suboptimal hybrid resource allocation (SHRA) for MLE are derived, respectively. The simulation results show that the proposed SORA and SHRA are flexible resource allocation strategies that adaptively arrange the resource based on the system parameters, and can have better estimation performance than other compared resource allocation strategies. Also, the proposed CIA schemes are shown to outperform the other compared schemes under the scenarios that include imperfect communication channels between the nodes and the FC.
Next, in the second part of the dissertation, we discuss the trade-off between energy conservation and estimation performance as it appears in the sequential CIA (SCIA) approach. In the SCIA approach, the strategy of sequential information forwarding is adopted instead of batch information forwarding. The fusion operation is based on the hard decision estimator and consisted of several sequentially executed voting processes. On the system initialization, each voting process is properly furnished with some ratio of resources, i.e. the information bits of the nodes, for the majority principle–based detection of its responsible bit in the quantized observation. Because the nodes sequentially forward their information bits to the FC, each voting process can be terminated when the majority is achieved after collecting partial information bits, and the nodes that are unneeded to forward their information bits are regarded as the unused resources in the voting process. Based on the different purposes regarding the management of the unused resources in each voting process, we design the energy-saving (ES) algorithm and the performance-improving (PI) algorithm for the SCIA approach, along with the analytical derivation for the total energy consumption of the ES algorithm. The presented simulation results reveal the effectiveness of the ES and PI algorithms on energy saving and performance improvement, respectively, in comparison with the CIA scheme using batch information forwarding. Also, the analytical solution for the total energy consumption of the ES algorithm is verified.
In the last part of the dissertation, motivated by improving the estimation performance of the original repetition codes–based CIA scheme, we investigate the incorporation of other more robust techniques of error correction codes. In considering the trade-off between enhancement of the error correction capability and suppression of the impact of observation noise, we apply the low-density generator matrix (LDGM) codes and propose the LDGM codes–based CIA scheme. In the LDGM codes–based CIA scheme, the generation of the forwarded bit at each node corresponds to a predetermined observation encoding process with very low computational complexity. In addition, considering the degradation of the error correction performance caused by the presence of short cycles in the generator matrix, we devise the construction for the generator matrix of the applied LDGM codes so that it is free from cycle of length 4. The simulation results show that the LDGM codes–based CIA scheme significantly outperforms the original repetition codes–based CIA scheme. Also, the robustness of the LDGM codes–based CIA scheme against the random death of nodes in the system is presented in the simulation.

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